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A PyTorch Toolbox for Face Recognition

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Hey, How can I import the pre-trained backbones that you share in Google Drive? Thank you!

when I add mask in folder used render_cy, sometimes I get error face mask ![1_133_add_8](https://user-images.githubusercontent.com/42052580/187013741-c3b14bab-373e-4ce8-a438-0470ead33d8d.jpg) ![1_150_add_6](https://user-images.githubusercontent.com/42052580/187013740-f91b0117-2bb9-4cb4-b8b0-42dc40c2f4e3.jpg) but when I rewrite this cython to a python function like def sim_render_cy(vertices, new_colors,...

Hi, Thanks for sharing, With face-down image, When I detect and align face, I have got issues: The landmark of face is wrong. Please help me check it ![test1_landmark_res0](https://user-images.githubusercontent.com/19282020/186459833-829636bb-566d-434c-9caf-e852ef73cd14.jpg)

Hello, if I want to add a mask to a cropped and aligned face image, what should I do? 你好,如果我想对经过裁剪对齐后的人脸图像添加口罩,我该怎么做

I added a basic installation file to the README to help users setup the API.

``` [handler_fileHandlers]]# fileHandlers class = logging.handlers.RotatingFileHandler level = DEBUG formatter = fmt args = ('logs/sdk.log', 'a', 10000, 3, 'UTF-8') ``` cause this error: ``` Traceback (most recent call last): File...

修改model_meta.json里的`model_file`改模型backbone,然后在lfw上测试效果很差,这是为什么呢? 0.19阈值: 0.5005008347245409 0.2阈值: 0.5003338898163606 0.21阈值: 0.5006677796327212 0.22阈值: 0.5003338898163606 0.23阈值: 0.5005008347245409 0.24阈值: 0.5010016694490818 0.25阈值: 0.5013355592654424 0.26阈值: 0.5020033388981636 0.27阈值: 0.5023372287145242 0.28阈值: 0.5028380634390651 0.29阈值: 0.5031719532554257 0.3阈值: 0.5030050083472454 0.31阈值: 0.5038397328881469 0.32阈值: 0.503338898163606 0.33阈值:...

DMUE. Did MobileNet, ShuffleNetV1, and ResNet50-IBN in Table 6 use pre-trained models? Can you provide a download link for the pre-trained models?

FaceDetModelHandler.py的55行已经推理出了5个关键点,为什么还要再用人脸对齐模型再检测一遍关键点,然后只用其中的5个点去crop人脸,不能用检测模型得到的5个点直接进行crop吗?

The `ImageDataset` class in `train.py` in conventional training folder: ```python class ImageDataset(Dataset): def __init__(self, data_root, train_file, crop_eye=False): self.data_root = data_root self.train_list = [] train_file_buf = open(train_file) line = train_file_buf.readline().strip() while...